In this paper we formulate overlapping clustering as the
problem of mapping each data point to a small set of labels
that represent cluster membership. The number of labels does
not have to be the same for all data points. The objective is to
find a mapping so that the similarity between any pair of points
in the dataset agrees as much as possible with the similarity
of their corresponding sets of labels.